What 300 Years Of Science Teach Us About WOM Metrics

In the early 18th century, scientists were fascinated with questions about the age of the earth. Geometry and experimentation had already provided clues to the size of the planet, and to the mass. But no one had yet figured out how old it was.

A few enterprising geologists began experimenting with ocean salinity. They measured the level of salt in the oceans as a benchmark, and then measured it every few months thereafter, believing that it might then be possible to work backwards to figure out how long it took to get to the present salinity level. Unfortunately, what they found was that the ocean salinity level fluctuates. So that approach didn't work.

In the 19th century, another group of geologists working the problem hypothesized that if the earth was once in fact a ball of molten lava, then it must have cooled to its current temperature over time. So they designed some experiments to heat various spheres to proportionate temperatures and then measure the rate of cooling. From this, they imagined, they could tell how long it took the earth to cool to its present temperature. Again, interesting approach, but it led to estimates that were in the range of 75,000 thousands of years. Skeptics argued that a quick look at the countryside around them provided evidence that those estimates couldn't possibly be correct. But the theory persisted for nearly 100 years!

Then in the early part of the 20th century, astronomers devised a new approach in estimating the age of the earth through radio spectroscopy. They studied the speed with which the stars were moving away from earth (by measuring shifts in light wave spectrum) and found there was a fairly uniform rate of speed. This allowed them to estimate that the earth was somewhere between 700 million and 1.2 billion years old. This seemed more plausible.

Not until 1956, shortly after the discovery of atomic half-lives, did physicists actually come up with the answer that we have today. When they studied various metals found in nature, they could measure the level of radiation in lead that had cooled from uranium, and then calculate backwards how long it had taken for radiation to achieve its present level. They estimated therefore that the earth was 4 to 5 billion years old.

Finally, in 1959, geologists discovered the Canyon Diablo meteorite, and the physicists realized that the earth must be older than the meteorite that hit it (seems logical). So they tool radiological readings from the meteorite and dated it at 4.53-4.58 billion years old.

Thus we presently believe our planet's age is somewhere in this range. It took the collective learnings of geologists, astronomers, and physicists (and a few chemists along the way) and over 250 years to crack the code. Thousands of man-years of experimentation traced some smart and some not-so-smart theories, but we got to an answer that seems like a sound estimate based on all available data.

Why torture you with the science lecture? Because there are so many parallels to where we are today with marketing measurement. We've only really been studying it for about 50 years now, and only intensely so for the past 30 years. We have many theories of how it works, and a great many people collecting evidence to test those theories. Researchers, statisticians, ethnographers, and academics of all types are developing and testing theories.

Still, at best, we are somewhere between cooling spheres and radio spectroscopy in our understanding of things. We're making best guesses based on our available science, and working hard to close the gaps and not get blinded by the easy answers.

I was reminded of this recently when I reviewed some of the excellent research done by Keller Fay Group in its TalkTrack® research, which interviews thousands of people each week to find out what they're talking about, and how that word-of-mouth (WOM) impacts brands. The research pretty clearly shows that only about 10% of total WOM activity occurs online. Further, it establishes that in MOST categories (not all, but most), the online chatter is NOT representative of what is happening offline, at kitchen tables and office water coolers.

Yet many of the "marketing scientists" are still confusing measurability and large data sets of online chatter for accurate information. It's a conclusion of convenience for many marketers. And one that is likely to be misleading and potentially career-threatening.

History is full of examples of how scientists were seduced by lots of data and wound up wandering down the wrong path for decades. Let's be cautious that we're not just playing with cooling spheres here. Scientific progress has always been built on triangulation of multiple methods. And while accelerating discoveries happen all the time though hard work, silver bullets are best left to the dreamers.

For the rest of us, it's back to the grindstone, testing our best hypotheses every day.

There is so much hype about social marketing, yet only 18 percent of the population is really using it based on our recent survey. Not all consumers are eager to log in and use Facebook. According to our recent study, twenty-seven percent of the population has never logged in to Facebook and another 20 percent only log in once or several times a month. That is 57 percent of the population that advertisers can miss out on. However, 38 percent log in daily and 16 percent several times a week. Who are these consumers? What should an advertiser know about these consumers to better engage them? Not surprisingly, consumers who are more likely to use Facebook are strong with the written word and are the most frequent users of the Internet. They use Facebook mostly to communicate with friends and connect with family. They like to keep their information up-to-date, meet new people, share photos, follow celebrities, share concerns, and solve problems. Most importantly, they like to learn about new products and share experiences about them.The segment of the population that frequents Facebook the most has the following characteristics:• Have great compassion for others and desire to be emotionally connected with others• Have a natural intuition about people and how to relate to them• Adapt well to change• Like to work with others• Are emotional, idealistic and romantic, yet can rationalize through situations• Enjoy gossip and messages delivered in story form and like to read and write• Do not require concrete examples in order to comprehend new ideasThese zealous consumers are only about 18 percent of the population and their marketing message is very different from other segments that have the opposite preferences.Another 32 percent of the population can also be attracted with emotional laden ads that incorporate family and friends, but this segment does not like to read, relate only to messages that show physical movement of people and tangible things, simply physical comedy, and their media preference is television or radio.That leaves another 59 percent of the population that responses to marketing messages that are very different and those consumers are not regularly logging into Facebook if at all. To better engage those messaging needs to …..Xyte has developed a segmentation system that is predictive and based on the way a person processes information, so we know much more about the consumer.

Roger Wilson from The Conference Department, Inc.,
March 16, 2010 at 3:11 p.m.

The ability to test their intuitions is one characteristic that separates the best media entreprenuers from the people who might get lucky once. A lot of what is being promoted about "new media" sounds plausible but has little empirical foundation. Human nature hasn't changed, and behavior hasn't changed as much as some of us would like to think. Media people are probably some of the biggest users of new media and we tend to make the mistake of thinking everybody is like us!

What you say is all true --except, we are not measuring physical phenomena, we are measuring social phenomena. The issue of WOM and online vs. other theaters for WOM can tell us only a couple of things: "How fast is it changing"? and "Is it getting closer or farther away?" This is helpful if you happen to know how your "interest" are "affected" by "velocity" and "direction." It's not subtle: it it moving toward me, or away? Is that good for me or bad for me." Like the "weather" and other complex adaptive systems you look for evidence of "change" in response to "actions". If I do "a" and expect to get "b," to I get "b"? Do I get it as soon as I expected? In the place I expected? Its more like sailing than it is like engineering. The problem with most people is they want "measurements" that lead to "certainty" while metrics in complex adaptive systems lead to "decisions" that lead to actions, that lead to revisions, that lead to new actions ...expecting your batting average to improve. In such case, very large sets of data are good.